lint

lint is a skill for Claude Code, Codex from darrencroton/ai-agent-coder. It costs 73 tokens per session (2,218 once invoked), scanned A, original, MIT.

A workflow for running fixed-rule code checks, such as detecting unused names, malformed tables, or formatting errors.

In plain words
What is it for?
Use it to lint changed files, check formatting or static analysis, and report only newly introduced findings.
Why use it?
It finds mechanical problems introduced by a change without relying on a reviewer’s opinion, while separating them from older findings.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/darrencroton/ai-agent-coder/lint
Any agent
npx skills add darrencroton/ai-agent-coder --skill lint
Clone the repo
git clone --depth 1 https://github.com/darrencroton/ai-agent-coder

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for lint

README.md
[![agentmods](https://agentmods.dev/badge/skills/darrencroton/ai-agent-coder/lint.svg)](https://agentmods.dev/skills/darrencroton/ai-agent-coder/lint)
Your own site
<a href="https://agentmods.dev/skills/darrencroton/ai-agent-coder/lint"><img src="https://agentmods.dev/badge/skills/darrencroton/ai-agent-coder/lint.svg" alt="Measured on agentmods" height="20"></a>
Per session 73 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,218 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00073 $0.02218
Opus 5 $0.00036 $0.01109
Sonnet 5 $0.00015 $0.00444
Haiku 4.5 $0.00007 $0.00222

Measured 5d ago against content hash ef29aac1dc75, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

lint scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/lint.py, tests/test_lint.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/lint/SKILL.md · 174 lines

How it starts

The opening of the file, as written. The whole thing — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Lint

Deterministic hygiene, run before any model-based review. The linters answer questions that have exact answers — unused name, unreachable branch, uninitialised read, malformed table, misspelt word, unformatted file — so no reviewer attention should be spent on them, and no reviewer's opinion is needed to settle them.

This skill exists because LLM reviewers are measurably bad at this class. Across five supervised runs of one plan, 11 of ~14 non-code-correctness findings were mechanical, and both commissioned reviewers missed every one of them while correctly finding subtle semantic defects. Lint is the cheap deterministic floor under review, not a replacement for it.

The one rule that makes this usable: differential by default

A gate that demands absolute cleanliness fails on arrival in any real repository, because pre-existing findings are not the current change's fault and fixing them is usually unauthorized scope.

So the default question is not "is this code clean?" but:

Does this change introduce a finding that was not there before?

check --base <ref> lints the changed files at the current head, lints the same files at <ref> in a throwaway worktree, and reports only the difference. Pre-existing debt cannot block; a newly added unused import cannot pass.

Use --all for absolute mode when you genuinely want every finding — a standalone audit, or a repo you are cleaning up.

Invariants

These are load-bearing. Do not work around them.

  1. check never installs anything. Installing mutates the machine. install is a separate, explicit, human-run subcommand, dry-run unless --yes is passed. An agent that finds a tool missing reports it and lets the human decide — it never runs install --yes on its own initiative, in any mode. check and detect name the missing binaries and print the install command so the human knows exactly what is needed.
  2. A missing linter is unavailable coverage, never a pass. The report names every language present with no tool available. --require-coverage turns that into exit 3 so an automated caller cannot mistake absence of findings for absence of problems.
  3. A failed run is an error, not a pass. A linter that exits unexpectedly with nothing parseable did not lint anything — an invalid ruff config exits 2 with empty output, which must never read as "0 findings". The same applies at the base ref, where a failure would make every pre-existing finding look new.
  4. Defects, not taste. The tool set is deliberately limited to findings with an objective answer. It carries no complexity metric, no naming opinion, and no architectural rule. A project's own conventions win: the linters read the project's own config files first, and config/ruff.toml and config/markdownlint.jsonc supply defect-focused defaults only when the project has none. Both exist because the tools' own defaults are broader than this rule allows — ruff's default set flags import ordering and rewrites config = dict(...) to a literal, which on one calibration repo was the documented convention of the project being linted. Shellcheck is capped at --severity=info for the same reason, dropping only its presentational style tier; a project's .shellcheckrc still selects which rules apply and shellcheck honours it regardless of that flag. If a plan mandates something a generic rule would flag, the plan is right and the rule must be skipped (--skip <tool>).
  5. Nothing is mutated. No --fix, no reformat-in-place. This skill reports; the Developer edits. (External tools may still write their own caches.)
  6. The comparison is a good heuristic, not an oracle. Signatures are line-insensitive, so a change that removes one finding and adds an equivalent one elsewhere in the same file nets out and is not reported. Tools that emit one finding per file — the formatters — cannot show a second regression in a file already unformatted at base. Absolute mode (--all) is the escape hatch when you need the whole picture.

Read the full file on GitHub · 174 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 174 lines · 73 tokens per session scan A ef29aac1dc75

Subscribe to this mod's changes

lint is a skill published in the GitHub repository darrencroton/ai-agent-coder (2 stars, last pushed 3d ago), licensed MIT. It adds 73 tokens to every session and 2,218 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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